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AWS Lambda 101: Infrastructure and Scaling

When to use Lambda and how to optimize your compute power

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What Is AWS Lambda?

Amazon Web Services has unveiled Lambda, a powerful and extremely cost-effective way to add power and scalability to your environment. Now you can just focus on developing your application without worrying about infrastructure, and stretch your IT budget by paying only for the compute time you actually use. Below are some keys to understanding what Lambda can do, options for using it, and maximizing its logging potential.

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AWS Lambda: Focus on developing applications without worrying about infrastructure.

The AWS Lambda service is a groundbreaking new way to run your applications in your AWS environment without worrying about underlying infrastructure such as CPU, memory or storage. The service enables you to upload your code–called a Lambda function–and configured it to execute under certain circumstances. Once in place, the Lambda function will operate as little or as frequently as its parameters indicate, and you will only pay for the actual processing time your function required.

Instances where Lambda functions can be used instead of server-based architecture include:

  • In application development. Write and execute code without the need to understand various AWS services required to run your application and without dealing with complexity of auto-scaling and infrastructure performance bottlenecks.
  • With Amazon S3. Run a Lambda function as soon as any new file gets uploaded to a specific S3 bucket.
  • With Amazon Kinesis. Trigger Lambda functions on specific logging events, such as new visitors to websites.
  • With AWS CloudTrail. Needle-like events logged in the haystack of Cloudtrail logs can launch a Lambda functions like enabling or disabling access permissions to resources like APIs and S3 storage buckets.

Not all programming languages are supported by AWS Lambda, but many popular programming languages and scripting languages, such as Java 8, Node.js (JavaScript), and Python, are supported. If you are a big C# shop, you may not be able to use AWS Lambda.

Smart Budgeting with AWS Lambda

With AWS Lambda’s serverless architecture and on-demand auto scaling features can grow or shrink network resources to match your traffic needs, all with no user intervention. This offers savings in potential compute overhead by pricing according to the total number of requests, and the amount of actual memory used in 100ms billing units. This ensures you only pay for precisely the amount of time that you use.

Channeling that knowledge into action is where time and costs can be cut substantially. Use your logs to monitor:

  • Total number of requests per Lambda function.
  • Resources needed to execute functions.
  • Average time from function call to execution.
  • Total Lambda error counts and detailed error per resource tracking.

Careful analysis of these metrics will open insights into where your IT dollars are going, where they can be saved, and where growth seems likely to require future investment.

Supercharge Log Analysis with Lambda Functions

AWS Lambda is at the forefront of a coming wave of serverless functionality and continuous auto scaling in dynamic network environments. Use Lambda reduce architecture overhead and optimize your operations. Create your free AWS account today, then get started with Lambda, and check out the Sumo Logic App for Lambda.

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